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| 1 | Overview of SMP-CAIL2020-Argmine:The Interactive Argument-Pair Extraction in Judgement Document Challenge显示文摘In this paper we present the results of the Interactive Argument-Pair Extraction in Judgement Document Challenge held by both the Chinese AI and Law Challenge(CAIL)and the Chinese National Social Media Processing Conference(SMP),and introduce the related data set-SMP-CAIL2020-Argmine.The task challenged participants to choose the correct argument among five candidates proposed by the defense to refute or acknowledge the given argument made by the plaintiff,providing the full context recorded in the judgement documents of both parties.We received entries from 63 competing teams,38 of which scored higher than the provided baseline model(BERT)in the first phase and entered the second phase.The best performing system in the two phases achieved accuracy of 0.856 and 0.905,respectively.In this paper,we will present the results of the competition and a summary of the systems,highlighting commonalities and innovations among participating systems.The SMP-CAIL2020-Argmine data set and baseline modelshave been already released. | Jian Yuan Zhongyu Wei Yixu Gao Wei Chen Yun Song Donghua Zhao Jinglei Ma Zhen Hu Shaokun Zou Donghai Li Xuanjing Huang | 2021 | Data Intelligence2021，3，2： | 3 |
| 2 | Identification of Chinese Materia Medicas in Microscopic Powder Images显示文摘This paper describes an identification system for Chinese Materia Medicas (CMMs) in microscopic powder images.The imaging processing of the microscopic powder image is very complex because of the low contrast,blurry boundaries,overlapping objects,and messy background.Therefore,the object detection must segment the significant microscopic structures from the complex image.The objects are detected in these images using an adaptable interactive method.After identifying the significant microscopic structures,the system identifies 14 features belonging to three main characteristics.These features form a 14-dimensional vector that represents the microscopic structures.The multi-dimensional vector is then analyzed using a feature assignment algorithm that picks the most notable features to construct a decision tree with thresholds.The identification system consists of a coarse classifier based on the decision tree and a fine classifier using similarity measurements to rank the possible results.Tests on 528 images from 24 different kinds of microscopic structures show the system effectiveness and applicability. | Shen Yan Yaoli Li Yixu Song Li Lin Peifa Jia Shaoqing Cai | 2012 | Tsinghua Science and Technology2012，17，2： | 2 |
| 3 | Development of a mobile application for identification of grapevine(Vitis vinifera L.)cultivars via deep learning显示文摘Traditional vine variety identification methods usually rely on the sampling of vine leaves followed by physical,physiological,biochemical and molecular measurement,which are destructive,time-consuming,labor-intensive and require experienced grape phenotype analysts.To mitigate these problems,this study aimed to develop an application(App)running on Android client to identify the wine grape automatically and in real-time,which can help the growers to quickly obtain the variety information.Experimental results showed that all Convolutional Neural Network(CNN)classification algorithms could achieve an accuracy of over 94%for twenty-one categories on validation data,which proves the feasibility of using transfer deep learning to identify grape species in field environments.In particular,the classification model with the highest average accuracy was GoogLeNet(99.91%)with a learning rate of 0.001,mini-batch size of 32,and maximum number of epochs in 80.Testing results of the App on Android devices also confirmed these results. | Yixue Liu Jinya Su Lei Shen Nan Lu Yulin Fang Fei Liu Yuyang Song Baofeng Su | 2021 | International Journal of Agricultural and Biological Engineering2021，14，5： | 1 |
| 4 | Short-term stock price prediction based on echo state networks显示文摘 | Lin Xiaowei Yang Zehong Song Yixu | 2009 | Expert Systems with Applications2009，36，3： | 1 |
| 5 | Intelligent control for a robot belt grinding system显示文摘 | Song Yixu Yang Hongjun Lv Hongbo | 2013 | Control Systems Technology IEEE Transactions on2013，21，3： | 1 |
| 6 | Plasma from healthy donors protects blood-brain barrier integrity via FGF21 and improves the recovery in a mouse model of cerebral ischaemia显示文摘Background Healthy plasma therapy reverses cognitive deficits and promotes neuroplasticity in ageing brain disease.However,whether healthy plasma therapy improve blood-brain barrier integrity after stroke remains unknown.Methods Here,we intravenously injected healthy female mouse plasma into adult female ischaemic stroke C57BL/6 mouse induced by 90 min transient middle cerebral artery occlusion for eight consecutive days.Infarct volume,brain atrophy and neurobehavioural tests were examined to assess the outcomes of plasma treatment.Cell apoptosis,blood-brain barrier integrity and fibroblast growth factor 21 knockout mice were used to explore the underlying mechanism.Results Plasma injection improved neurobehavioural recovery and decreased infarct volume,brain oedema and atrophy after stroke.Immunostaining showed that the number of transferase dUTP nick end labelling+/NeuN+cells decreased in the plasma-injected group.Meanwhile,plasma injection reduced ZO-1,occluding and claudin-5 tight junction gap formation and IgG extravasation at 3 days after ischaemic stroke.Western blot results showed that the FGF21 expression increased in the plasma-injected mice.However,using FGF21 knockout mouse plasma injecting to the ischaemic wild-type mice diminished the neuroprotective effects.Conclusions Our study demonstrated that healthy adult plasma treatment protected the structural and functional integrity of blood-brain barrier,reduced neuronal apoptosis and improved functional recovery via FGF21,opening a new avenue for ischaemic stroke therapy. | Muyassar Mamtilahun Lu Jiang Yaying Song Xiaojing Shi Chang Liu Yixu Jiang Lidong Deng Haoran Zheng Hui Shen Yongfang Li Zhijun Zhang Yongting Wang Yaohui Tang Guo-Yuan Yang | 2021 | Stroke & Vascular Neurology2021，6，4： | 1 |
| 7 | Back to Science in Searching for SARS-CoV-2 Origins显示文摘In recent decades,emerging and re-emerging human-infecting pathogens have been represented as huge threats to public health and have become a global concern(1).After outbreaks of two coronaviruses(CoVs),severe acute respiratory syndrome coronavirus(SARS-CoV)and Middle East respiratory syndrome coronavirus(MERS-CoV),severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)became the first-known pandemic hastening CoV with tremendous wrecking to the world(2).The origin tracing of these emerging pathogens is of great significance in infectious disease prevention and control(3–4).The origin of SARS-CoV-2 remains elusive after the more than 3-year pandemic,though scientists around the world are making great efforts.From the experience of studying many other infectious pathogens,origin tracing is systematic and time-consuming work.The supposed origins of many infectious pathogens are still in debate,including SARS-CoV and human immunodeficiency virus,etc(5). | William J Liu Wenwen Lei Xiaozhou He Peipei Liu Qihui Wang Zhiqiang Wu Yun Tan Shuhui Song Gary Wong Jian Lu Jingkun Jiang Qiang Wei Mingkun Li Juncai Ma Xiaozhong Peng Yixue Li Baoxu Huang Yigang Tong Jun Han Guizhen Wu | 2023 | China CDC weekly2023，5，14： | 0 |
| 8 | Study of wafer pre-aligning approaches显示文摘 | 李世昌 Zhao Yannan Song Yixu Yang Zehong Wang Jiaxin | 2007 | High Technology Letters2007，13，3： | 0 |
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